Traditional techniques for providing searching capabilities, such as for web-based searching, have been developed principally to serve users having work station-like computing devices and monitors, including desktop computing devices, laptop computing devices, and the like. These computing devices have sufficient resources, such as display area of a monitor or a liquid crystal display (“LCD”) flat panel, to convey information to facilitate searching of a collection of data entities in a database. In ecommerce applications, for instance, search processes typically are established to facilitate searching via the above-identified computing devices for products in catalog databases, and traditional arrangements of data and data relationships. While functional, there is a variety of drawbacks associated with the conventional approaches to searching for data entities.
FIG. 1A illustrates a conventional data arrangement for supporting traditional approaches to searching databases. Data are arranged in a hierarchical data structure 101 having various levels of data relationships (e.g., levels of parent-child relationships), including level (“1”) 103a, level (“2”) 103b, and level (“3”) 103c. In tree-like data structure 101, a catalog is arranged in various nested levels of categories, each of which terminates in a set of data files for a set of products. A conventional approach to search for products organized in accordance with hierarchical data structure 101 requires a user to repeatedly select categories in which to drill down into until a set of product data files is discoverable. If the user has not discovered a desired product, the user is required usually to return to a higher-level of hierarchy to reiterate drilling down through other branches of the data structure 101 in search of the desired product.
FIG. 1B illustrates an interface 100 used to generate or transition among a series of windows typically used in traditional search techniques, including on-line or web-based searching. Generally, as a user causes typical search algorithms to move up and down levels of tree-like data structure 101, the changes between levels 103a, 103b, and 103c invoke generation of (or transition to) a window, or portion thereof (e.g., an HTML iframe). In a typical catalog search process, a window 102 is shown to a user in response to a request (not shown) to search a catalog of footwear data files. Window 102 includes a representation, such as link (“Next”) 104, which can be a link associated with a category that is selectable. Window 102 transitions to window 112 when the user selects link 104. The user then is presented in this illustration with window (“Popular footwear”) 112 from which additional categories can be selected in accordance with data structures of a conventional web-based catalog system 115 to facilitate on-line searches of product catalogs. Window 112 includes a depiction of a representation 113 of a first type of shoe. Consider that the user has a moderate amount of interest in the first type of shoe. But in accordance with conventional search techniques, a user might experience a transition back to window 102 if the user desires to review information regarding the higher-level information regarding footwear that is associated with window 112. Such transitions disrupt the user's experience and search process. Further, the user might experience a delay before being able to proceed to the next step of the search process, which typically resumes with transition from either window 102 or 112, by selecting a category associated with either link 104 or link 106. Again, the user traditionally experiences another transition to window (“Men's Footwear”) 122 to search through a more specific set of product files. Yet again, a user encounters further disruptions and delays when the interface transitions to another window 132 (e.g., upon selection of a category associated with link 108), should, for example, the user desires to review information regarding men's dress shoes. Window 132 includes a depiction of a representation 133 of a second type of shoe. At this point in the search, the user might have an interest in the second type of shoe, but typically must rely on the recollection of the first type of shoe when comparing and contrasting products to select between the two shoe types for making a purchase. Transitioning back to a window that contains information about the first type of shoe might be difficult for the user to do based on the user's recollection and usually takes additional time.
The back-and-forth nature of conventional search processes usually requires that the user interact with two or more windows 102, 112, 122, and 132, which interrupts the user experience during searching. Users also experience numerous visual transitions, disruptions and delays in the process of searching a conventional product catalog. It is also expected that, after each stage, some users decide not to continue with the relatively cumbersome search process, resulting in the loss of potential customers or customers and less favorable conversions.
In view of the foregoing, it is be desirable to provide an apparatus, a system, and a method for overcoming the drawbacks of the conventional deposition processes to search data structures for a record of interest.